Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
Communications of the ACM - Special issue on analysis and modeling in software development
Identifying controlling features of engineering design iteration
Management Science
Organizational Learning: Creating, Retaining, and Transferring Knowledge
Organizational Learning: Creating, Retaining, and Transferring Knowledge
Information and Organizations
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Introduction to the Algebraic Theory of Graph Grammars (A Survey)
Proceedings of the International Workshop on Graph-Grammars and Their Application to Computer Science and Biology
Organizational Routines as a Source of Continuous Change
Organization Science
Designing Work Within and Between Organizations
Organization Science
Evolving Work Routines: Adaptive Routinization of Information Technology in Healthcare
Information Systems Research
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Variability in organizational work processes is believed to influence productivity, quality, flexibility, and a host of other aspects of organizational design and management, but this construct has never been clearly conceptualized and measured. This paper introduces the concept of sequential variety, which accounts for variability in the sequence of events or actions that make up a process. This paper also proposes and compares three measures of sequential variety in organizational processes: Average distance (based on optimal string matching), algorithmic complexity, and deviation from uniform, random Markov. These measures are compared and validated using a simulated data set that embodies the range of variation likely to be encountered in empirical studies. All three measures correlate well and provide useful indicators of sequential variety, but the measures based on optimal string matching and deviation from the uniform, random Markov seem likely to be more useful in various potential applications.